pl_sales_report.py in Python

Build a monthly sales summary from raw transactions.

"""Build a monthly sales summary from raw transactions with Polars."""
import polars as pl


def build_report(transactions):
    df = pl.DataFrame(transactions)
    return (
        df
        .with_columns(
            (pl.col("units") * pl.col("price")).alias("revenue"),
            pl.col("date").str.slice(0, 7).alias("month"),
        )
        .group_by("month", "product")
        .agg(
            pl.col("revenue").sum().round(2).alias("revenue"),
            pl.col("units").sum().alias("units"),
        )
        .sort("revenue", descending=True)
    )


def main():
    transactions = [
        {"date": "2026-06-03", "product": "kea", "units": 4, "price": 9.5},
        {"date": "2026-06-19", "product": "tui", "units": 2, "price": 12.0},
        {"date": "2026-07-02", "product": "kea", "units": 7, "price": 9.5},
        {"date": "2026-07-21", "product": "tui", "units": 5, "price": 12.0},
    ]
    report = build_report(transactions)
    print(report)
    print(f"total revenue: {report['revenue'].sum():.2f}")


if __name__ == "__main__":
    main()

How it works

1. Expressions derive revenue and a month column.
2. group_by aggregates revenue and units.
3. The report sorts by revenue and totals it.

Keywords and builtins used here

• as
• build_report
• def
• if
• main
• print
• return

The run, in numbers

Lines

35

Characters to type

897

Tokens

320

Three-star pace

115 tpm

At the three-star pace of 115 tokens a minute, this run takes about 167 seconds.

Type this snippet

Step 1 of 2 in Encore, step 31 of 32 in Polars.

← Previous Next →